Data Analyst Interview Questions in India (SQL, Power BI & MIS) — 2026 Edition

How Data Analyst interviews work in India

Most interviews have 3–4 rounds:

1. HR screening — background, salary, notice period
2. Technical — SQL, Excel, Power BI (often a test or live questions)
3. Case study / assignment — take-home dashboard or SQL test
4. Manager round — domain fit, communication, stakeholder handling

This guide covers questions from each round with simple sample answers.

SQL interview questions

Q1: What is the difference between WHERE and HAVING?

Simple answer: WHERE filters rows before grouping. HAVING filters after GROUP BY.

-- WHERE: filter individual orders
SELECT Region, SUM(Sales) AS Total
FROM Orders
WHERE OrderDate >= '2026-01-01'
GROUP BY Region;

-- HAVING: filter grouped results
SELECT Region, SUM(Sales) AS Total
FROM Orders
GROUP BY Region
HAVING SUM(Sales) > 100000;

Q2: Explain INNER JOIN vs LEFT JOIN

• INNER JOIN — only matching rows from both tables
• LEFT JOIN — all rows from left table + matches from right (NULL if no match)

Use LEFT JOIN when you need to find missing relationships (e.g. customers with no orders).

Q3: How do you find duplicate records?

SELECT Email, COUNT(*) FROM Customers
GROUP BY Email HAVING COUNT(*) > 1;

Q4: What is a window function?

A calculation across related rows without collapsing the result into one row.

Example: rank employees by salary within each department using RANK() OVER (PARTITION BY department ORDER BY salary DESC).

Power BI interview questions

Q5: Import vs DirectQuery?

• Import — data copied into Power BI (faster visuals, scheduled refresh)
• DirectQuery — queries live database (always current, can be slower)

Use Import for most MIS dashboards under a few million rows.

Q6: What is a measure vs a calculated column?

• Measure — calculated on the fly (SUM, AVG, ratios) — use for KPIs
• Calculated column — computed row by row, stored in the table — use for labels/categories

Q7: How do you handle slow dashboards?

• Reduce imported columns
• Use SQL views for pre-aggregation
• Remove unnecessary visuals
• Check relationship cardinality
• Use Performance Analyzer in Power BI

Excel / MIS questions

Q8: VLOOKUP vs INDEX-MATCH?

Both lookup values. INDEX-MATCH is more flexible (lookup left or right, handles insert/delete better). In modern Excel, XLOOKUP is preferred.

Q9: What is Power Query?

Excel's tool to connect, clean, and refresh data from databases and files. Mention you use it to automate weekly MIS instead of manual copy-paste.

Case study questions

Q10: "Sales dropped 15% this month. How would you investigate?"

Use the structured approach:

1. Confirm the number — check SQL query, date filters, duplicates
2. Segment — by region, product, channel, customer type
3. Compare time — vs last month, same month last year
4. Check external factors — holidays, stock-outs, price changes
5. Recommend action — with data-backed hypothesis

Interviewers care about your thinking process, not a perfect answer.

Behavioral questions (STAR method)

Q11: Tell me about a time you improved a report process.

STAR template:

• Situation: Manual Excel report took 4 hours weekly
• Task: Reduce time and errors
• Action: Built SQL view + Power Query pipeline + Power BI dashboard
• Result: Cut time to 45 minutes, fewer revision requests from management

Q12: How do you handle unclear requirements?

Sample answer: "I schedule a 15-minute call to confirm the decision the stakeholder needs, list proposed KPIs, share a draft, and iterate before building the full dashboard."

Questions to ask the interviewer

• What tools does the team use daily?
• How is success measured in the first 90 days?
• What does the data stack look like (SQL Server, cloud, ERP)?
• Is there opportunity to work on automation and dashboards?

1-week interview prep plan

Final takeaway

Indian Data Analyst interviews test practical skills — SQL, Excel, Power BI, and clear communication. Practice explaining your projects simply, and always connect technical work to business impact (time saved, faster decisions, fewer errors).